Diffusion MRI is a magnetic resonance imaging (MRI) method that produces in vivo images of biological tissues weighted with the local microstructural characteristics of water diffusion and is capable of showing connections between brain regions. In the presence of a magnetic field gradient, diffusion of water molecules leads to signal loss in MR images. The degree of signal loss depends on the characteristics of the diffusion, which in turn depends on tissue properties like structure, surrounding environment, physical state and pathology. The use of MR to probe such tissue properties based on water diffusion is called diffusion imaging. The magnetic field gradient used to probe tissue diffusion is called a diffusion gradient. The amount of signal loss during diffusion imaging depends on the dimensionless product: Db, where D is the diffusion coefficient in mm2/sec, and b is a factor in sec/mm2 which depends on the characteristics of the diffusion gradient. There are different methods of varying the magnitude and direction of the diffusion gradient to reconstruct a complete picture of the tissue properties. Such methods are called diffusion encoding methods. Diffusion imaging is usually performed with 2D multi-slice echo-planar imaging (EPI) based methods. The total scan time for such methods for human imaging can range from 1-30 minutes based on the type of diffusion encoding method used. For such long scans, bulk subject motion is a problem. In diffusion neuroimaging, problems occurring due to patient motion include, i) images acquired with different diffusion directions are misaligned, leading to erroneous calculation of diffusion parameters, and ii) images being acquired in a diffusion direction when motion occurs are susceptible to MR signal dropouts. Multiple known systems, both retrospective and prospective, attempt to address this problem with limited success. A system according to invention principles comprehensively addresses this problem and related problems.